Methods and systems disclosed herein relate generally to noninvasive methods to evaluate the anisotropic properties of fibrous structures such as neuronal pathways in the human brain (white matter) and muscle for diagnostic purposes.
It is known that the material parameters (such as stiffness and viscosity) of human tissue are affected by injury and disease. For example, the stiffness of both gray and white matter decreases in patients with Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), and Alzheimer's Disease (AD). Similarly, in patients with muscular degeneration and myocardial infarction, there are distinct differences in the fiber architecture and stiffness. Therefore, it is of interest to provide a methodology for the noninvasive evaluation and diagnosis of these conditions that improve upon current techniques.
Previously-developed methods to noninvasively evaluate the material parameters of human tissue typically use knowledge of elastic displacements provided by a single measurement modality (such as Ultrasound (US) or Magnetic Resonance Elastography (MRE)) and an isotropic Helmholtz inversion algorithm. Romano, A., et al., Evaluation of a Material Parameter Extraction Algorithm using MRI-Based Displacement Measurements, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency control, 2000; 47: 1575-1581; and Oliphant, T. et al., Complex-valued Stiffness Reconstruction for Magnetic Resonance Elastography by Algebraic Inversion of the Differential Equation, Magnetic Resonance in Medicine, 2001; 45: 299-310.
These are reasonable approaches for media which are isotropic (meaning that the material stiffness constants are the same in every direction and are represented by two elastic coefficients, one longitudinal and one shear). However, if the medium is comprised of fibers such as muscle and white matter pathways, it is considered to be anisotropic, meaning that waves propagate within these structures as if they were waveguides and the material stiffness constants depend upon the symmetry of the fibrous structures and elastic wave velocities depend on the direction of wave propagation through them. Within media such as these, the material constants can number from three to twenty-one, requiring more sophisticated inversion methods for their evaluation. In addition to knowledge of the elastic displacements in three dimensions, these latter methods require knowledge of the orientation of these waveguides in space as well as appropriate anisotropic inversion algorithms which are lacking in currently available approaches.
Waveguide Elastography (WGE) combines diffusion tensor imaging (DTI), MRE, spatial-spectral filtering, a Helmholtz decomposition, and inversions for the assessment of the anisotropic elastic constants of fibrous structures, and was demonstrated in the Corticospinal Tracts (CSTs) of five healthy human volunteers (Romano, A., et al., In Vivo Waveguide Elastography of White Matter Tracts in the Human Brain, Magnetic Resonance in Medicine, 2012; 68: 1410-1422.). Specifically, DTI was used to evaluate the fiber pathways of the CSTs which have been observed to act as waveguides for externally induced wave propagation. 3D-vector field MRE was performed at the same spatial resolution and voxel position achieved by DTI in order to track the propagation of waves traveling at specific angles to the fiber directions. Using this waveguide methodology, the viscoelastic properties of the CSTs were analyzed using an orthotropic material model comprised of nine independent elastic constants. Redundancies in the solutions for the orthotropic coefficients indicated that the CSTs could be well represented by hexagonal anisotropy (transverse isotropy) comprised of five independent elastic constants.
The previously described method was also applied to a cohort of 28 volunteers, 14 of which had been diagnosed with ALS and 14 of which were healthy, age matched controls (Romano, A., et al., In Vivo Waveguide Elastography: Effects of Neurodegeneration in Patients with Amyotrophic Lateral Sclerosis, Magnetic Resonance in Medicine, 2013; DOI 10.1002/mrm.25067). ALS is a rapidly progressive neurodegenerative disease affecting the upper and lower motor neuron with an average life expectancy of only about 2-3 years after symptom onset. The diagnosis of ALS is currently based largely on clinical signs. Both upper and lower motor neuron involvement have to be present to confirm the diagnosis. However, especially the assessment of upper motor neuron involvement can be difficult from clinical signs alone. Hence, there is an ongoing search for reliable biomarkers in ALS. Currently, neuroimaging is performed to rule out any pathologies that could mimic ALS symptoms. Conventional MRI is, in the majority of patients, unremarkable especially at an early stage of the disease. Certain imaging signs/features, e.g. a T2-hyperintensity of the CST or a signal reduction in the primary motor cortex can sometimes be observed in ALS patients, but these signs are neither very sensitive nor specific for ALS. More advanced methods, e.g. Magnetization Transfer Imaging (MTI) and metrics derived from Diffusion Tensor Imaging (DTI) (such as fractional anisotropy (FA), parallel diffusivity (PD), mean diffusivity (MD), and radial diffusivity (RD)) are evaluated as biomarkers for the detection of upper motor neuron involvement and show promising results.
What is needed, however, is a system that evaluates appropriate dynamic models and associated viscoelastic constants in arbitrarily curved anisotropic biological media. In this latter study, when compared to healthy controls, it was found that the stiffness of the CSTs of the patients with ALS was significantly reduced due to neurodegeneration of the myelin sheaths.